A Feedback Belief Propagation Algorithm for LDPC Convolutional Codes
Yuanhua Liu, Xinmei Wang, Yucheng He · 2008
A feedback belief propagation (BP) decoding algorithm for low-density parity-check convolutional codes is proposed. The proposed algorithm can activate the variable nodes more efficiently by applying feedback decoding at each decoding iteration. Compared with the on-demand BP algorithm, the proposed algorithm has a doubled convergence speed and causes only about half of the decoding delay at similar error performances without any increase of storage requirement. Simulation results show that the proposed algorithm can offer a good trade-off between the error-correcting performance and the decoding complexity.